Mean Biases Dominate CMIP6 Model Deficiencies in Simulating Heavy Rainfall During Monsoon Intraseasonal Oscillation

Abstract The monsoon intraseasonal oscillation (MISO) modulates heavy precipitation during the Indian summer monsoon, but accurate rainfall simulation remains a challenge in state‐of‐the‐art models. Our analysis reveals a moisture bias in MISO using simulations from the sixth phase of the Coupled Model Intercomparison Project models. Despite an overestimated local moisture supply from the ocean in the Bay of Bengal (BoB), atmospheric moisture content before MISO‐induced heavy rainfall is underestimated. Model diagnoses reveal deficient zonal moisture advection in the low‐level troposphere as the primary constraint, attributable to a weaker intraseasonal Arabian Sea moisture source and a bias in the mean zonal winds. The latter inhibits the development of barotropic instability and the energy transfer to intraseasonal timescales. Consequently, the weakly simulated MISO leads to insufficient moisture supply over the BoB, resulting in failed simulation of heavy rainfall during MISO events. These findings highlight potential approaches for model improvements to enhance monsoon precipitation simulations.